Extend the Ant Colony Optimization Algorithm for virtualization Technologies to improve the Resources utilization in On-Premises Datacenters

Authors

  • Jean Claude HABINSHUTI MUHUMUZA University of Kigali, RWANDA
  • Emmanuel BUGINGO University of Kigali, RWANDA
  • Célestin Tshimanga Kamanga University of Kinshasa, Kinshasa, Democratic Republic of Congo

DOI:

https://doi.org/10.53819/81018102t7000

Abstract

Over the past few decades, there has been an increasing demand for computational power, which has fueled the growth of on-premises data centers. In recent years, virtualization techniques have been introduced to enhance data center resource utilization. These techniques consolidate multiple workloads onto fewer servers, reducing the need for physical devices to support an organization's IT infrastructure. Virtualization technologies have increased IT agility by allowing for quicker deployment of virtual machines (VMs), which in turn facilitates faster application and service rollouts, improves disaster recovery capabilities, and reduces carbon emissions, leading to significant cost savings for organizations. In this paper, we enhance the Ant Colony Optimization Algorithm (ACO) by applying it to virtualization. We simulate the ACO for virtual machine resource management. Our evaluation results demonstrate that the proposed algorithm can further improve resource utilization and reduce carbon emissions.

Keywords: Virtualization, Datacenter, Resource utilization, Ant Colony Optimization.

Author Biographies

Jean Claude HABINSHUTI MUHUMUZA, University of Kigali, RWANDA

School of Computing, and Information Technology University of Kigali, RWANDA

Emmanuel BUGINGO, University of Kigali, RWANDA

School of Business and Economics, Department of Business and Information Technology, University of Rwanda, RWANDA

Célestin Tshimanga Kamanga, University of Kinshasa, Kinshasa, Democratic Republic of Congo

School of Mathematics and Computer Sciences, University of Kinshasa, Kinshasa, Democratic Republic of Congo

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Published

2024-02-22

How to Cite

MUHUMUZA, J. C. H., BUGINGO, E., & Kamanga, C. T. (2024). Extend the Ant Colony Optimization Algorithm for virtualization Technologies to improve the Resources utilization in On-Premises Datacenters. Journal of Information and Technology, 8(1), 28–42. https://doi.org/10.53819/81018102t7000

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Articles